* Change to directory with files*
use "cyk_main_experiments_combined.dta", clear
* Scheme graphs were made in *
set scheme s2color

* APPENDIX FIGURES *

* Figure B1: Replicating Figure 1 with Logistic Regression *
logit support i.exp_group gop5 dem5 female age education white rule_of_law 
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
marginsplot, horizontal graphregion(color(white)) ti("") yscale(range(.5 2.5)) yti("") xti(" " "Difference in Support") ylabel(1 "Zone 3 Treatment" 2 "Zone 1 Treatment") recast(scatter) recastci(rspike) plotopts(mcolor(black)) ciopts(lcolor(black)) xline(0) xlabel(-.06 "-6%" -.04 "-4%" -.02 "-2%" 0 "0%" .02 "2%" .04 "4%" .06 "6%") saving("effects_all.gph", replace)
* test referenced in text *
ttest support if treat_zone1 == 1|treat_zone3 == 1, by(treat_zone1)

* Figure B2: Treatment effects by category Using Logistic Regression *
use "cyk_main_experiments_combined.dta", clear
gen n = _n
gen diff = .
gen l = .
gen u = .
gen sediff = .
gen treatment = .

logit support i.exp_group gop5 dem5 female age education white rule_of_law  if hypothetical == 1
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,3] if n == 6
replace sediff = r(table)[2,3] if n == 6
replace treatment = 1 if n == 6
replace diff = r(table)[1,2] if n == 5
replace sediff = r(table)[2,2] if n == 5
replace treatment = 0 if n == 5
logit support control treat_zone1 gop5 dem5 female age education white rule_of_law  if hypothetical == 1
margins, dydx(treat_zone1)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,1] if n == 4
replace sediff = r(table)[2,1] if n == 4
replace treatment = 3 if n == 4

logit support i.exp_group gop5 dem5 female age education white rule_of_law  if distant == 1
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,3] if n == 3
replace sediff = r(table)[2,3] if n == 3
replace treatment = 1 if n == 3
replace diff = r(table)[1,2] if n == 2
replace sediff = r(table)[2,2] if n == 2
replace treatment = 0 if n == 2
logit support control treat_zone1 gop5 dem5 female age education white rule_of_law  if distant == 1
margins, dydx(treat_zone1)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,1] if n == 1
replace sediff = r(table)[2,1] if n == 1
replace treatment = 3 if n == 1

logit support i.exp_group gop5 dem5 female age education white rule_of_law  if recent == 1
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,3] if n == 9
replace sediff = r(table)[2,3] if n == 9
replace treatment = 1 if n == 9
replace diff = r(table)[1,2] if n == 8
replace sediff = r(table)[2,2] if n == 8
replace treatment = 0 if n == 8
logit support control treat_zone1 gop5 dem5 female age education white rule_of_law  if recent == 1
margins, dydx(treat_zone1)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,1] if n == 7
replace sediff = r(table)[2,1] if n == 7
replace treatment = 3 if n == 7

replace l = diff-1.96*(sediff)
replace u = diff+1.96*(sediff)
replace n = . if n > 9
recode n (1=1.7) (3=2.3) (4=4.7) (6=5.3) (7=7.7) (9=8.33) 
twoway (dot  diff n if treatment == 1, horizontal ndots(0) dcolor(white) symbol(triangle) color(black)) ///
(dot  diff n if treatment == 0, horizontal ndots(0) dcolor(white) symbol(square) color(black)) ///
(dot  diff n if treatment == 3, horizontal ndots(0) dcolor(white) symbol(circle_hollow) color(gs5)) ///
(rspike u l n if treatment ==0|treatment==1, horizontal color(black)) ///
(rspike u l n if treatment ==3, horizontal color(gs5)), yti("") graphregion(color(white)) ///
xline(0) xlabel(-.1 "-10%" -.05 "-5%" 0 "0%" .05 "5%" .1 "10%" .15 "15%") xline(0) ///
ylabel( 2 "Clinton or Bush" 8 "Biden or Trump" 5 "Hypothetical", angle(0)) /// 
legend(order( 1 "Zone 1 Treatment" 2 "Zone 3 Treatment" 3 "Zone 1 - Zone 3") size(small) keygap(3) symx(.85) cols(3))   yscale(range(.5 9.5)) 

* Figure B3: Comparing Treatment Effects across Hypotheticals with Logistic Regression *
use "cyk_main_experiments_combined.dta", clear
gen n = _n
gen diff = .
gen l = .
gen u = .
gen sediff = .
gen treatment = .

logit support i.exp_group gop5 dem5 female age education white rule_of_law  if experiment == 7
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,3] if n == 6
replace sediff = r(table)[2,3] if n == 6
replace treatment = 1 if n == 6
replace diff = r(table)[1,2] if n == 5
replace sediff = r(table)[2,2] if n == 5
replace treatment = 0 if n == 5
logit support control treat_zone1 gop5 dem5 female age education white rule_of_law  if experiment == 7
margins, dydx(treat_zone1)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,1] if n == 4
replace sediff = r(table)[2,1] if n == 4
replace treatment = 3 if n == 4

logit support i.exp_group gop5 dem5 female age education white rule_of_law  if experiment == 10
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,3] if n == 3
replace sediff = r(table)[2,3] if n == 3
replace treatment = 1 if n == 3
replace diff = r(table)[1,2] if n == 2
replace sediff = r(table)[2,2] if n == 2
replace treatment = 0 if n == 2
logit support control treat_zone1 gop5 dem5 female age education white rule_of_law  if experiment == 10
margins, dydx(treat_zone1)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,1] if n == 1
replace sediff = r(table)[2,1] if n == 1
replace treatment = 3 if n == 1

logit support i.exp_group gop5 dem5 female age education white rule_of_law  if experiment == 4
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,3] if n == 9
replace sediff = r(table)[2,3] if n == 9
replace treatment = 1 if n == 9
replace diff = r(table)[1,2] if n == 8
replace sediff = r(table)[2,2] if n == 8
replace treatment = 0 if n == 8
logit support control treat_zone1 gop5 dem5 female age education white rule_of_law  if experiment == 4
margins, dydx(treat_zone1)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,1] if n == 7
replace sediff = r(table)[2,1] if n == 7
replace treatment = 3 if n == 7

logit support i.exp_group gop5 dem5 female age education white rule_of_law  if experiment == 3
margins, dydx(exp_group)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,3] if n == 12
replace sediff = r(table)[2,3] if n == 12
replace treatment = 1 if n == 12
replace diff = r(table)[1,2] if n == 11
replace sediff = r(table)[2,2] if n == 11
replace treatment = 0 if n == 11
logit support control treat_zone1 gop5 dem5 female age education white rule_of_law  if experiment == 3
margins, dydx(treat_zone1)  at(gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
replace diff = r(table)[1,1] if n == 10
replace sediff = r(table)[2,1] if n == 10
replace treatment = 3 if n == 10

replace l = diff-1.96*(sediff)
replace u = diff+1.96*(sediff)
replace n = . if n > 12
recode n (1=1.7) (3=2.3) (4=4.7) (6=5.3) (7=7.7) (9=8.33) 

twoway (dot  diff n if treatment == 1, horizontal ndots(0) dcolor(white) symbol(triangle) color(black)) ///
(dot  diff n if treatment == 0, horizontal ndots(0) dcolor(white) symbol(square) color(black)) ///
(dot  diff n if treatment == 3, horizontal ndots(0) dcolor(white) symbol(circle_hollow) color(gs5)) ///
(rspike u l n if treatment ==0|treatment==1, horizontal color(black)) ///
(rspike u l n if treatment ==3, horizontal color(gs5)), yti("") graphregion(color(white)) ///
xline(0) xlabel(-.15 "15%" -.1 "-10%" -.05 "-5%" 0 "0%" .05 "5%" .1 "10%" .15 "15%" .2 "20%") xline(0) ///
ylabel( 8 `" "Hypothetical Mexico Loan" "(Unilateral Control)" "' 5 `" "Hypothetical Mexico Loan" "(Legislative Control)" "' 2 "Hypothetical Student Loans" 11 "Hypothetical Platinum Coin", angle(0)) /// 
legend(order( 1 "Zone 1 Treatment" 2 "Zone 3 Treatment" 3 "Zone 1 - Zone 3") size(small) keygap(2) symx(.85) cols(3))   yscale(range(.5 12.5)) 

* Figure B4: Treatment Effects for Recent Presidents *
use "cyk_main_experiments_combined.dta", clear
gen n = _n
gen diff = .
gen l = .
gen u = .
gen sediff = .
gen treatment = .

reg support treat_zone1 treat_zone3 if experiment == 2
replace diff = _b[treat_zone1] if n == 6
replace sediff = _se[treat_zone1] if n == 6
replace treatment = 1 if n == 6
replace diff = _b[treat_zone3] if n == 5
replace sediff = _se[treat_zone3] if n == 5
replace treatment = 0 if n == 5
reg support control treat_zone1 if experiment == 2
replace diff = _b[treat_zone1] if n == 4
replace sediff = _se[treat_zone1] if n == 4
replace treatment = 3 if n == 4

reg support treat_zone1 treat_zone3 if experiment == 8
replace diff = _b[treat_zone1] if n == 3
replace sediff = _se[treat_zone1] if n == 3
replace treatment = 1 if n == 3
replace diff = _b[treat_zone3] if n == 2
replace sediff = _se[treat_zone3] if n == 2
replace treatment = 0 if n == 2
reg support control treat_zone1 if experiment == 8
replace diff = _b[treat_zone1] if n == 1
replace sediff = _se[treat_zone1] if n == 1
replace treatment = 3 if n == 1

reg support treat_zone1 treat_zone3 if experiment == 1
replace diff = _b[treat_zone1] if n == 9
replace sediff = _se[treat_zone1] if n == 9
replace treatment = 1 if n == 9
replace diff = _b[treat_zone3] if n == 8
replace sediff = _se[treat_zone3] if n == 8
replace treatment = 0 if n == 8
reg support control treat_zone1 if experiment == 1
replace diff = _b[treat_zone1] if n == 7
replace sediff = _se[treat_zone1] if n == 7
replace treatment = 3 if n == 7

replace l = diff-1.96*(sediff)
replace u = diff+1.96*(sediff)
replace n = . if n > 9
recode n (1=1.7) (3=2.3) (4=4.7) (6=5.3) (7=7.7) (9=8.33) 
twoway (dot  diff n if treatment == 1, horizontal ndots(0) dcolor(white) symbol(triangle) color(black)) ///
(dot  diff n if treatment == 0, horizontal ndots(0) dcolor(white) symbol(square) color(black)) ///
(dot  diff n if treatment == 3, horizontal ndots(0) dcolor(white) symbol(circle_hollow) color(gs5)) ///
(rspike u l n if treatment ==0|treatment==1, horizontal color(black)) ///
(rspike u l n if treatment ==3, horizontal color(gs5)), yti("") graphregion(color(white)) ///
xline(0) xlabel(-.15 "15%" -.1 "-10%" -.05 "-5%" 0 "0%" .05 "5%" .1 "10%" .15 "15%") xline(0) ///
ylabel( 2 "Biden Student Loans" 8 "Trump Wall" 5 "Biden Platinum Coin", angle(0)) /// 
legend(order( 1 "Zone 1 Treatment" 2 "Zone 3 Treatment" 3 "Zone 1 - Zone 3") size(small) keygap(3) symx(.85) cols(3))   yscale(range(.5 9.5)) 

* Figure B5: Treatment Effects for Temporally Distant Presidents *
use "cyk_main_experiments_combined.dta", clear
gen n = _n
gen diff = .
gen l = .
gen u = .
gen sediff = .
gen treatment = .

reg support treat_zone1 treat_zone3 if experiment == 6
replace diff = _b[treat_zone1] if n == 6
replace sediff = _se[treat_zone1] if n == 6
replace treatment = 1 if n == 6
replace diff = _b[treat_zone3] if n == 5
replace sediff = _se[treat_zone3] if n == 5
replace treatment = 0 if n == 5
reg support control treat_zone1 if experiment == 6
replace diff = _b[treat_zone1] if n == 4
replace sediff = _se[treat_zone1] if n == 4
replace treatment = 3 if n == 4

reg support treat_zone1 treat_zone3 if experiment == 9
replace diff = _b[treat_zone1] if n == 3
replace sediff = _se[treat_zone1] if n == 3
replace treatment = 1 if n == 3
replace diff = _b[treat_zone3] if n == 2
replace sediff = _se[treat_zone3] if n == 2
replace treatment = 0 if n == 2
reg support control treat_zone1 if experiment == 9
replace diff = _b[treat_zone1] if n == 1
replace sediff = _se[treat_zone1] if n == 1
replace treatment = 3 if n == 1

reg support treat_zone1 treat_zone3 if experiment == 5
replace diff = _b[treat_zone1] if n == 9
replace sediff = _se[treat_zone1] if n == 9
replace treatment = 1 if n == 9
replace diff = _b[treat_zone3] if n == 8
replace sediff = _se[treat_zone3] if n == 8
replace treatment = 0 if n == 8
reg support control treat_zone1 if experiment == 5
replace diff = _b[treat_zone1] if n == 7
replace sediff = _se[treat_zone1] if n == 7
replace treatment = 3 if n == 7

replace l = diff-1.96*(sediff)
replace u = diff+1.96*(sediff)
replace n = . if n > 9
recode n (1=1.7) (3=2.3) (4=4.7) (6=5.3) (7=7.7) (9=8.3) 
twoway (dot  diff n if treatment == 1, horizontal ndots(0) dcolor(white) symbol(triangle) color(black)) ///
(dot  diff n if treatment == 0, horizontal ndots(0) dcolor(white) symbol(square) color(black)) ///
(dot  diff n if treatment == 3, horizontal ndots(0) dcolor(white) symbol(circle_hollow) color(gs5)) ///
(rspike u l n if treatment ==0|treatment==1, horizontal color(black)) ///
(rspike u l n if treatment ==3, horizontal color(gs5)), yti("") graphregion(color(white)) ///
xline(0) xlabel(-.15 "15%" -.1 "-10%" -.05 "-5%" 0 "0%" .05 "5%" .1 "10%" .15 "15%") xline(0) ///
ylabel( 2 `" "Clinton Mexico Loan" "(Unilateral Control)" "' 8 `" "Clinton Mexico Loan" "(Legislative Control)" "' 5 "Bush Tribunals", angle(0)) /// 
legend(order( 1 "Zone 1 Treatment" 2 "Zone 3 Treatment" 3 "Zone 1 - Zone 3") size(small) keygap(3) symx(.85) cols(3))   yscale(range(.5 9.5)) 

* Figure B6: ROL Moderation Using 4-Point DV"
reg support4 i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4) gop5=0 dem5=0 female=1 education =3 age=43 white = 1 rule_of_law=3)
marginsplot, recast(line) recastci(rarea) ti("All") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_all4.gph", replace)

reg support4 i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & recent == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Biden or Trump") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_recent4.gph", replace) ylabel(-.1 0 .1 .2)

reg support4 i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & hypothetical == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hypothetical4.gph", replace) ylabel(-.1 0 .1 .2)

reg support4 i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & distant == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Clinton or Bush") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_distant4.gph", replace) ylabel(-.1 0 .1 .2)
graph combine "rol_all4.gph" "rol_recent.gph" "rol_hypothetical.gph" "rol_distant.gph", graphregion(color(white)) rows(2) 

* Figure D1: ROL Moderation for Recent President Vignettes*
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Trump Wall") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_trump_Wall.gph", replace) ylabel(-.1 0 .1 .2)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 2
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Biden Platinum Coin") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_biden_coin.gph", replace) ylabel(-.1 0 .1 .2)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 8
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Biden Student Loans") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_biden_student.gph", replace) ylabel(-.1 0 .1 .2)
graph combine "rol_trump_Wall.gph" "rol_biden_coin.gph" "rol_biden_student.gph", graphregion(color(white)) rows(3) xsize(8.5) ysize(11)

* Figure D2: ROL Moderation for Temporally Distant Vignettes *
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 5
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Clinton Mexico Loan" "(Unilateral Control)") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_clinton_mexico_ua.gph", replace) ylabel(-.1 0 .1 .2)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 6
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Bush Tribunals") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_bush_tribunals.gph", replace) ylabel(-.1 0 .1 .2)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 9
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Clinton Mexico Loan" "(Legislative Control)") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_clinton_mexico_leg.gph", replace) ylabel(-.1 0 .1 .2)
graph combine "rol_clinton_mexico_ua.gph" "rol_bush_tribunals.gph" "rol_clinton_mexico_leg.gph", graphregion(color(white)) rows(3) xsize(8.5) ysize(11)

* Figure D3: ROL Moderation for Hypothetical Vignettes *
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 3
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical Platinum Coin") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hyp_coin.gph", replace) ylabel(-.2 -.1 0 .1)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 4
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical Mexico Loan" "(Unilateral Control)") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hyp_loan_ua.gph", replace) ylabel(-.1 0 .1 .2 .3)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 7
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical Mexico Loan" "(Legislative Control)") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hyp_loan_leg.gph", replace) ylabel(-.2 -.1 0 .1 .2 .3)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 10
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical Student Loans") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hyp_student_loans.gph", replace) ylabel(-.2 -.1 0 .1)

graph combine "rol_hyp_coin.gph" "rol_hyp_loan_ua.gph" "rol_hyp_loan_leg.gph" "rol_hyp_student_loans.gph", graphregion(color(white)) rows(2) 

* Figure E1: Treatment Effects across 6 Experiments then 4 follow-ups*
use "cyk_first_survey_data_combined.dta", clear
reg support i.exp_group
margins, dydx(exp_group)
marginsplot, horizontal graphregion(color(white)) ti("UA Control Experiments") yscale(range(.5 2.5)) yti("") xti(" " "Difference in Support") ylabel(1 "Zone 3 Treatment" 2 "Zone 1 Treatment") recast(scatter) recastci(rspike) plotopts(mcolor(black)) ciopts(lcolor(black)) xline(0) xlabel(-.06 "-6%" -.04 "-4%" -.02 "-2%" 0 "0%" .02 "2%" .04 "4%" .06 "6%") saving("effects_all.gph", replace)
* test referenced in text *
ttest support if treat_zone1 == 1|treat_zone3 == 1, by(treat_zone1)
use "cyk_second_survey_data_combined.dta", replace
reg support i.exp_group
margins, dydx(exp_group)
marginsplot, horizontal graphregion(color(white)) ti("Legislative Control Experiments") yscale(range(.5 2.5)) yti("") xti(" " "Difference in Support") ylabel(1 "Zone 3 Treatment" 2 "Zone 1 Treatment") recast(scatter) recastci(rspike) xline(0) xlabel(-.08 "-8%"-.06 "-6%" -.04 "-4%" -.02 "-2%" 0 "0%" .02 "2%" .04 "4%" .06 "6%")saving("effects_all_followup.gph", replace) plotopts(mcolor(black)) ciopts(lcolor(black))
* test referenced in text *
ttest support if treat_zone1 == 1|treat_zone3 == 1, by(treat_zone1)
graph combine "effects_all.gph" "effects_all_followup.gph", rows(2) graphregion(color(white)) xsize(8.5) ysize(11)

* Figure E2: Treatment Effect by Vignette Type by Category of Experiment *
use "cyk_first_survey_data_combined.dta", clear
gen n = _n
gen diff = .
gen l = .
gen u = .
gen sediff = .
gen treatment = .

reg support treat_zone1 treat_zone3 if recent == 1
test treat_zone1 = treat_zone3
replace diff = _b[treat_zone1] if n == 8
replace sediff = _se[treat_zone1] if n == 8
replace treatment = 1 if n == 8
replace diff = _b[treat_zone3] if n == 7
replace sediff = _se[treat_zone3] if n == 7
replace treatment = 0 if n == 7

reg support treat_zone1 treat_zone3 if hypothetical == 1
test treat_zone1 = treat_zone3
replace diff = _b[treat_zone1] if n == 5
replace sediff = _se[treat_zone1] if n == 5
replace treatment = 1 if n == 5
replace diff = _b[treat_zone3] if n == 4
replace sediff = _se[treat_zone3] if n == 4
replace treatment = 0 if n == 4

reg support treat_zone1 treat_zone3 if distant == 1
test treat_zone1 = treat_zone3
replace diff = _b[treat_zone1] if n == 2
replace sediff = _se[treat_zone1] if n == 2
replace treatment = 1 if n == 2
replace diff = _b[treat_zone3] if n == 1
replace sediff = _se[treat_zone3] if n == 1
replace treatment = 0 if n == 1

replace l = diff-1.96*(sediff)
replace u = diff+1.96*(sediff)
replace n = . if n > 8
recode n (1=1.25) (2=1.75) (4=4.25) (5=4.75) (7=7.25) (8=7.75)
twoway (dot  diff n if treatment == 1, horizontal ndots(0) dcolor(white) symbol(triangle) color(black)) ///
(dot  diff n if treatment == 0, horizontal ndots(0) dcolor(white) symbol(square) color(black)) ///
(rspike u l n, horizontal color(black)), yti("") graphregion(color(white)) ///
xline(0) xlabel(-.1 "-10%" -.05 "-5%" 0 "0%" .05 "5%" .1 "10%") xline(0) ///
ylabel(7.5 "Biden or Trump" 4.5 "Hypothetical" 1.5 "Clinton or Bush", angle(0)) /// 
legend(order( 1 "Zone 1 Treatment" 2 "Zone 3 Treatment") size(medsmall) keygap(0) colgap(.5) cols(2))   yscale(range(0 9)) saving("category_first.gph", replace) scale(.8) ti("Unilateral Control Experiments")
* Follow-up Experiments*
use "cyk_second_survey_data_combined.dta", replace
gen n = _n
gen diff = .
gen l = .
gen u = .
gen sediff = .
gen treatment = .

reg support treat_zone1 treat_zone3 if experiment == 4
test treat_zone1 = treat_zone3
replace diff = _b[treat_zone1] if n == 11
replace sediff = _se[treat_zone1] if n == 11
replace treatment = 1 if n == 11
replace diff = _b[treat_zone3] if n == 10
replace sediff = _se[treat_zone3] if n == 10
replace treatment = 0 if n == 10

reg support treat_zone1 treat_zone3 if experiment == 2
test treat_zone1 = treat_zone3
replace diff = _b[treat_zone1] if n == 8
replace sediff = _se[treat_zone1] if n == 8
replace treatment = 1 if n == 8
replace diff = _b[treat_zone3] if n == 7
replace sediff = _se[treat_zone3] if n == 7
replace treatment = 0 if n == 7

reg support treat_zone1 treat_zone3 if experiment == 1
test treat_zone1 = treat_zone3
replace diff = _b[treat_zone1] if n == 5
replace sediff = _se[treat_zone1] if n == 5
replace treatment = 1 if n == 5
replace diff = _b[treat_zone3] if n == 4
replace sediff = _se[treat_zone3] if n == 4
replace treatment = 0 if n == 4

reg support treat_zone1 treat_zone3 if experiment == 3
test treat_zone1 = treat_zone3
replace diff = _b[treat_zone1] if n == 2
replace sediff = _se[treat_zone1] if n == 2
replace treatment = 1 if n == 2
replace diff = _b[treat_zone3] if n == 1
replace sediff = _se[treat_zone3] if n == 1
replace treatment = 0 if n == 1

replace l = diff-1.96*(sediff)
replace u = diff+1.96*(sediff)
replace n = . if n > 11
recode n (1=1.25) (2=1.75) (4=4.25) (5=4.75) (7=7.25) (8=7.75) (10=10.25) (11=10.75)
twoway (dot  diff n if treatment == 1, horizontal ndots(0) dcolor(white) symbol(triangle) color(black)) ///
(dot  diff n if treatment == 0, horizontal ndots(0) dcolor(white) symbol(square) color(black)) ///
(rspike u l n, horizontal color(black)), yti("") graphregion(color(white)) ///
xline(0) xlabel(-.15 "-15%" -.1 "-10%" -.05 "-5%" 0 "0%" .05 "5%" .1 "10%") xline(0) ///
ylabel(10.5 "Hypothetical Student Loan Debt" 7.5 "Biden Student Loan Debt" 4.5 "Hypothetical Mexcio Loan" 1.5 "Clinton Mexico Loan", angle(0)) /// 
legend(order( 1 "Zone 1 Treatment" 2 "Zone 3 Treatment") size(medsmall) keygap(0) cols(2)) scale(.8)  yscale(range(0 12)) saving("follow_effect.gph", replace) ti("Legislative Control Experiments")
grc1leg2 "category_first.gph" "follow_effect.gph", rows(2) graphregion(color(white)) xsize(8.5) ysize(11)

* Figure E3: Rule of Law Moderation Across Experiment Types *
use "cyk_first_survey_data_combined.dta", clear
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_all.gph", replace) ti("Unilateral Control Experiments")
use "cyk_second_survey_data_combined.dta", replace
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_all_followup.gph", replace) ti("Legislative Control Experiments")
graph combine "rol_all.gph" "rol_all_followup.gph", graphregion(color(white)) rows(2) xsize(8.5) ysize(11)

* Figure E4: ROL Moderation by Vignette Type -- Unilateral Control Experiments *
use "cyk_first_survey_data_combined.dta", clear
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & recent == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Biden or Trump") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_recent.gph", replace) ylabel(-.1 0 .1 .2)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & hypothetical == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hypothetical.gph", replace) ylabel(-.1 0 .1 .2)

reg support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & distant == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Clinton or Bush") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_distant.gph", replace) ylabel(-.1 0 .1 .2)
graph combine "rol_recent.gph" "rol_hypothetical.gph" "rol_distant.gph", graphregion(color(white)) rows(3) xsize(8.5) ysize(11)

* Figure E5: ROL Moderation by Experiment -- Legislative Control Experiments *
use "cyk_second_survey_data_combined.dta", replace
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 1
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical Mexico Loan") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hypo_mexico.gph", replace)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 2
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Biden Student Loans") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_biden_studentloans.gph", replace)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 3
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Clinton Mexico Loan") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_clinton_mexico.gph", replace)

logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & experiment == 4
margins, dydx(treat_zone1) at(rule_of_law=(1(.1)4))
marginsplot, recast(line) recastci(rarea) ti("Hypothetical Student Loans") ///
xtitle("Rule of Law Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("rol_hypo_studentloans.gph", replace)

graph combine "rol_hypo_studentloans.gph" "rol_biden_studentloans.gph"  "rol_hypo_mexico.gph" "rol_clinton_mexico.gph" , graphregion(color(white)) rows(2)

* Figure E6: Treatment Effects by Attention *
* Effects by Attention *
use "cyk_mechanisms_survey.dta", replace
* Color screener *
gen color_passed = 0
replace color_passed = 1 if color_3 == 1&color_5==1&color_1==.&color_2==.&color_4==.&color_6==.
* Neither agree nor disagree screener *
gen neither_passed = 0
replace neither_passed = 1 if statements_2 == 3
* WWII screener *
gen WWII_passed = 0
replace WWII_passed = 1 if statements_4 == 5
* Newspaper screener *
gen newspaper_passed =0
replace newspaper_passed = 1 if newspaper_5==1&newspaper_11 == 1&newspaper_1==.&newspaper_2==.&newspaper_3==.&newspaper_4==.&newspaper_6==.&newspaper_7==.&newspaper_8==.&newspaper_9==.&newspaper_10==.&newspaper_12==.

* Regressions for those who passed each filter individually *
logit trib_supp_bin trib_zone1 trib_zone3 gop5 dem5 female education age white rule_of_law
logit trib_supp_bin trib_zone1 trib_zone3 gop5 dem5 female education age white rule_of_law if color_passed == 1
logit trib_supp_bin trib_zone1 trib_zone3 gop5 dem5 female education age white rule_of_law if neither_passed == 1
logit trib_supp_bin trib_zone1 trib_zone3 gop5 dem5 female education age white rule_of_law if WWII_passed == 1
logit trib_supp_bin trib_zone1 trib_zone3 gop5 dem5 female education age white rule_of_law if newspaper_passed == 1

logit loan_supp_bin loan_zone1 loan_zone3 gop5 dem5 female education age white rule_of_law
logit loan_supp_bin loan_zone1 loan_zone3 gop5 dem5 female education age white rule_of_law if color_passed == 1
logit loan_supp_bin loan_zone1 loan_zone3 gop5 dem5 female education age white rule_of_law if neither_passed == 1
logit loan_supp_bin loan_zone1 loan_zone3 gop5 dem5 female education age white rule_of_law if WWII_passed == 1
logit loan_supp_bin loan_zone1 loan_zone3 gop5 dem5 female education age white rule_of_law if newspaper_passed == 1

logit wall_supp_bin wall_zone1 wall_zone3 gop5 dem5 female education age white rule_of_law
logit wall_supp_bin wall_zone1 wall_zone3 gop5 dem5 female education age white rule_of_law if color_passed == 1
logit wall_supp_bin wall_zone1 wall_zone3 gop5 dem5 female education age white rule_of_law if neither_passed == 1
logit wall_supp_bin wall_zone1 wall_zone3 gop5 dem5 female education age white rule_of_law if WWII_passed == 1
logit wall_supp_bin wall_zone1 wall_zone3 gop5 dem5 female education age white rule_of_law if newspaper_passed == 1

* Create attention factor score *
factor color_passed neither_passed WWII_passed newspaper_passed
predict factor_attention

logit trib_supp_bin i.trib_zone1##c.factor_attention gop5 dem5 female education age white rule_of_law if trib_zone1==1|trib_zone3==1
margins, dydx(trib_zone1) at(factor_attention=(-1.5(.1)1) gop5=0 dem5=0 female=0 education =3 age=45 white = 1 rule_of_law=3)
marginsplot, recast(line) recastci(rarea) ti("Bush Tribunals") ///
xtitle("Attentiveness Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("trib_attention.gph", replace) ylabel(-.2 -.1 0 .1 .2 .3 .4)

logit loan_supp_bin i.loan_zone1##c.factor_attention gop5 dem5 female education age white rule_of_law if loan_zone1==1|loan_zone3==1
margins, dydx(loan_zone1) at(factor_attention=(-1.5(.1)1) gop5=0 dem5=0 female=0 education =3 age=45 white = 1 rule_of_law=3)
marginsplot, recast(line) recastci(rarea) ti("Hypothetical Mexico Loan") ///
xtitle("Attentiveness Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("loan_attention.gph", replace) ylabel(-.2 -.1 0 .1 .2 .3 .4)

logit wall_supp_bin i.wall_zone1##c.factor_attention gop5 dem5 female education age white rule_of_law if wall_zone1==1|wall_zone3==1
margins, dydx(wall_zone1) at(factor_attention=(-1.5(.1)1) gop5=0 dem5=0 female=0 education =3 age=45 white = 1 rule_of_law=3)
marginsplot, recast(line) recastci(rarea) ti("Trump Wall") ///
xtitle("Attentiveness Index") graphregion(color(white)) yline(0, lpattern(dash)) ci1opts(color(gs10%70)) plotopts(lcolor(black)) yti("Zone1 vs. Zone 3" " ") saving("wall_attention.gph", replace) ylabel(-.2 -.1 0 .1 .2 .3 .4)

graph combine "loan_attention.gph" "trib_attention.gph" "wall_attention.gph", graphregion(color(white)) rows(3) xsize(8.5) ysize(11) 

* Figure G1: Effect of Treatments on Perceptions of Supreme Court Striking Down Action *
use "cyk_mechanisms_survey.dta", replace

gen n = _n
gen bz1 = .
gen u = .
gen l = .
gen bz3 = .
gen treatment = .

reg wall_legal wall_zone1 wall_zone3 gop5 dem5 female age education white rule_of_law 
replace bz1 = r(table)[1,1] if n == 1
replace u = r(table)[6,1] if n == 1
replace l = r(table)[5,1] if n == 1
replace bz3 = r(table)[1,2] if n == 2
replace u = r(table)[6,2] if n == 2
replace l = r(table)[5,2] if n == 2

reg trib_court trib_zone1 trib_zone3 gop5 dem5 female age education white rule_of_law 
replace bz1 = r(table)[1,1] if n == 4
replace u = r(table)[6,1] if n == 4
replace l = r(table)[5,1] if n == 4
replace bz3 = r(table)[1,2] if n == 5
replace u = r(table)[6,2] if n == 5
replace l = r(table)[5,2] if n == 5

reg loan_court loan_zone1 loan_zone3 gop5 dem5 female age education white rule_of_law 
replace bz1 = r(table)[1,1] if n == 7
replace u = r(table)[6,1] if n == 7
replace l = r(table)[5,1] if n == 7
replace bz3 = r(table)[1,2] if n == 8
replace u = r(table)[6,2] if n == 8
replace l = r(table)[5,2] if n == 8

replace n = . if n > 8
recode n (1=1.25) (2=1.75) (4=4.25) (5=4.75) (7=7.25) (8=7.75)

twoway (dot  bz1 n , horizontal ndots(0) dcolor(white) symbol(triangle) color(black)) ///
(dot  bz3 n, horizontal ndots(0) dcolor(white) symbol(square) color(black)) ///
(rspike u l n, horizontal color(black)), yti("") graphregion(color(white)) ///
xline(0) ylabel(7.5 "Hypothetical Mexico Loan" 4.5 "Bush Tribunals" 1.5 "Border Wall", angle(0)) /// 
legend(order( 1 "Zone 1 Treatment" 2 "Zone 3 Treatment") size(medsmall) keygap(0) colgap(.5) cols(2)) xlabel(-.4 -.3 -.2 -.1 0 .1 .2 .3 .4)  yscale(range(0 9)) ti("", size(medium)) scale(.8) saving(scotus_beliefs.gph, replace)

* APPENDIX TABLES *

* Table B1 *
use "cyk_main_experiments_combined.dta",  clear
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law 
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label replace
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 5
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 6
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 9
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 3
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 4
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 7
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 10
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 1
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 2
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append
reg support4 treat_zone1 treat_zone3 gop5 dem5 female age education white rule_of_law if experiment == 8
test treat_zone1=treat_zone3
outreg2 using sitable_ols, word dec(2) label append

* Table C1 *
use "cyk_main_experiments_combined.dta", clear
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1
outreg2 using sitable3, word dec(2) label replace
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & recent == 1
outreg2 using sitable3, word dec(2) label append
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & hypothetical == 1
outreg2 using sitable3, word dec(2) label append
logit support i.treat_zone1##c.rule_of_law gop5 dem5 female age education white rule_of_law if exp_group !=1 & distant == 1
outreg2 using sitable3, word dec(2) label append

* Table C2 *
use "cyk_main_experiments_combined.dta", clear
gen party3 = .
replace party3=1 if dem5==1
replace party3 = 2 if dem5 == 0 & gop5 == 0
replace party3 = 3 if gop5 == 1

* Note: exp_group2 is Zone 3 treatment and exp_group3 is Zone 1 treatment *
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 1
outreg2 using sitable5, word dec(2) label replace
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 2
outreg2 using sitable5, word dec(2) label append
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 3
outreg2 using sitable5, word dec(2) label append
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 4
outreg2 using sitable5, word dec(2) label append
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 5
outreg2 using sitable5, word dec(2) label append
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 6
outreg2 using sitable5, word dec(2) label append

* Table C3 *
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 7
outreg2 using sitable6, word dec(2) label replace
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 8
outreg2 using sitable6, word dec(2) label append
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 9
outreg2 using sitable6, word dec(2) label append
logit support exp_group##i.party3 female age education white rule_of_law if experiment == 10
outreg2 using sitable6, word dec(2) label append
* Note: order is presented differently in Table *

* Table C4: Regressions of Treatment Effects on Beliefs and Support *
use "cyk_mechanisms_survey.dta", replace
reg loan_legal loan_zone1 loan_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label replace
reg loan_cong loan_zone1 loan_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append
logit loan_supp_bin loan_zone1 loan_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append

reg trib_legal trib_zone1 trib_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append
reg trib_cong trib_zone1 trib_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append
logit trib_supp_bin trib_zone1 trib_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append

reg wall_legal wall_zone1 wall_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append
reg wall_cong wall_zone1 wall_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append
logit wall_supp_bin wall_zone1 wall_zone3 gop5 dem5 female age education white rule_of_law 
outreg2 using sitable7, word dec(2) label append









* Analyses with 4-point DV *


